Prognostic Decision Making to extend a platform useful life under service constraint

Abstract

This paper adresses the problem of optimizing the useful life of a heterogeneous distributed platform which has to produce a given production service. The purpose is to provide a production scheduling that maximizes the production horizon. The use of Prognostics and Health Management (PHM) results in the form of Remaining Useful Life (RUL) allows to adapt the schedule to the wear and tear of equipment. This work comes within the scope of Prognostics Decision Making (DM). Each considered machine is supposed to be able to provide several throughputs corresponding to different operating conditions. The key point is to select the appropriate profile for each machine during the whole useful life of the platform. Many heuristics are proposed to cope with this decision problem and are compared through simulation results. Simulations assess the efficiency of these heuristics. Distance to the theoretical maximal value comes close to 10% for the most efficient ones. A repair module performing a revision of the schedules provided by the heuristics is moreover proposed to enhance the results. First results are promising.